Why Prioritizing Empathy and Emotional Understanding Drives Success

The term emotional intelligence was coined by Peter Salovey and John D. Mayer in 1990. They defined EQ as a set of skills hypothesized to contribute to the accurate appraisal and expression of emotion in oneself and in others, the effective regulation of emotion in self and others, and the use of feelings to motivate, plan and achieve in one’s life.

Emotional Intelligence entails an important underlying proposition: that the emotional systems that inform our conscious state have a direct effect on productivity, success, and functioning. This thesis goes beyond the western tendency toward enlightenment thinking that’s dominated Western thought from the 1700s until today. Rene Descartes, often thought of as the father of early modern philosophy famously stated: I think, therefore I am. He proceeded to conduct a series of thought experiments from which he claimed that the ability to form rational thoughts is what makes us quintessentially human.

After several hundred years and troves of valuable research by psychologists, cognitive scientists, and neuroscientists, emotion is claiming a new domain for itself in the workplace. In a recent list generated by the World Economic Forum of top ten skills employees will need to thrive in the future workplace, emotional intelligence ranked sixth. Another study by psychologists at Miami University found that EQ has a positive correlation to employees’ financial success. According to Emotional Intelligence 2.0 author Travis Bradberry, “EQ is so critical to success that it accounts for 58 percent of performance in all types of jobs.”

So what is it that makes emotional intelligence so important now? It’s no secret that a slew of new technologies are helping humans perform better at their jobs, and may even replace humans at routine, manual tasks. This ongoing process of automation is expected to continue thanks to a trifecta of influences. First, robots and computers are capable of outperforming humans at some physical labor for a cheaper price. Second, government-backed programs such as China’s, which has made it the world’s largest consumer of industrial robots, are providing the capital and political backing to more rapidly transform the workforce worldwide. Finally, the brightest minds in tech are innovating the processes that make up our everyday lives at an incredible level. Automated technologies are disrupting many different sectors of the economy, from self-driving vehicles to AI-powered healthcare technologies, and customer service enhancement.

Check out our podcast on the Future of Work hosted by RapportBoost.AI Chief Data Scientist Michael Housman and Roy Bahat of Bloomberg Beta

Automation doesn’t mean that humans will lose their jobs to robots – it means that humans will need to become skilled at jobs that can’t be done by their machine counterparts. These jobs are often in the service industry and require high EQ. According to a November 2017 McKinsey report on the future of work, by 2030 3 to 14% of global workers will need to switch occupational categories and adapt alongside machines to occupy positions that “require social and emotional skills, creativity, high-level cognitive capabilities and other skills relatively hard to automate”.

As machines get smarter, emotional intelligence remains a difficult skill set to teach. Part of this difficulty lies in what robotics refers to as the uncanny valley. When humans interact with AI-powered entities, there’s an ongoing process that takes place in which a human bridges the divide between themselves and the AI. Once the AI slips up, eliciting an incorrect phrase or skipping a beat in the natural conversational technique of turn-taking, the human realizes the AI isn’t real. This epiphany may prompt negative emotions of betrayal or disgust, and most often causes the human to no longer want to interact with her AI counterpart.

The other huge challenge that AI developers face is replicating human empathy in machines. Humans convey emotion through highly unique facial expressions, vocal tone, and body language. Our high-EQ colleagues and life partners pick up on these cues and make instantaneous adjustments to the way they interact with us – a process that forms the basis of a healthy relationship. Teaching this sort of empathy to machines is limited by several factors: a lack of accurate data that correlates to emotional cues, and data privacy and ethics issues that will surface as companies seek to gain this information from consumers, employees, and customers. As the process of workforce automation continues, emotional intelligence and the skills it encompasses will continue to be a crucial – and quintessentially human – competence.

There’s a bounty of research that shows that EQ is crucial to the workforce and organizational efficiency. A 2017 study on the interaction of employees and managers found that those managers and employees who exhibited stronger emotional intelligence tendencies through expressive facial expressions were more competent at handling a conversation addressing performance review conversation. Furthermore, the leaders who exhibit high EQ inspire team members to work more efficiently to achieve organizational goals. Up until the recent conversation about EQ, there had been a lack of research on the positive correlation between EQ and the corporate world.

While data-centric aspects of medical, legal and customer service professions may be handled by machines, it’s empathetic competencies that comprise the difference between a sales associate and an enterprise salesperson, a doctor and a community leader, and a corporate employee and a CEO. By prioritizing empathy and emotional understanding at every level of the organization – from training to performance review and the behavior of leaders – organizations can nurture an environment that drives toward success.

About Dani Apgar

Danielle is a Co-Founder of RapportBoost.AI, and one of the world’s most successful enterprise artificial intelligence sales professionals. She led the sales, customer success, account management, and sales engineering teams for more than 3 years at Persado, a CNBC Disruptor Top 50 Artificial Intelligence company funded by Goldman Sachs and Bain Capital.
She has personally closed six and seven-figure artificial intelligence/SaaS/ARR deals with Microsoft, Travelocity, Caesars Entertainment, Pottery Barn, and Zulily. Her clients had the highest rate of customer retention and satisfaction in the 200+ person company. Dani first worked with Tony in a Silicon Valley tech company in 1999.